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A New Technique for Lossless Compression of Color Images Based on Hierarchical Prediction, Inversion and Context Adaptive Coding

机译:基于分层预测,反演和上下文自适应编码的彩色图像无损压缩新技术

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This work introduces a new technique for lossless compression of color images. The technique is composed of first transforming an RGB image into luminance and chrominance domain (Y CuCv). Then, the luminance channel Y is compressed with a context-based, adaptive, lossless image coding technique (CALIC). After processing the chrominance channels with a hierarchical prediction technique that was introduced by Kim and Cho, Burrows-Wheeler Inversion Coder (BWIC) or JPEG 2000 is used to compress of the chrominance channels Cu and Cv. It is demonstrated that, on a wide variety of images, particularly on medical images, the technique achieves substantial compression gains over other well-known compression schemes such as CALIC, JPEG 2000, LOCO-I, BPG(HEVC), and the previously proposed hierarchical prediction and context adaptive coding technique LCIC.
机译:这项工作介绍了一种用于无损压缩彩色图像的新技术。该技术包括首先将RGB图像转换为亮度和色度域(Y CuCv)。然后,使用基于上下文的自适应无损图像编码技术(CALIC)压缩亮度通道Y。用Kim和Cho引入的分层预测技术处理色度通道后,使用Burrows-Wheeler反转编码器(BWIC)或JPEG 2000压缩色度通道Cu和Cv。已经证明,在各种各样的图像上,特别是在医学图像上,该技术比其他众所周知的压缩方案(例如,CALIC,JPEG 2000,LOCO-I,BPG(HEVC)和先前提出的压缩方案)获得了可观的压缩增益。分层预测和上下文自适应编码技术LCIC。

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